Publications | ROB.AI-Lab.Science | Chair of Cyber-Physical-Systems

Publication List with Images

2020
Tanneberg, Daniel; Rueckert, Elmar; Peters, Jan Evolutionary training and abstraction yields algorithmic generalization of neural computers Journal Article In: Nature Machine Intelligence, pp. 1–11, 2020. Links \| BibTeX \| Tags: neural network, Reinforcement Learning, Transfer Learning @article{Tanneberg2020, title = {Evolutionary training and abstraction yields algorithmic generalization of neural computers}, author = {Daniel Tanneberg and Elmar Rueckert and Jan Peters }, url = {https://rdcu.be/caRlg, Article File}, doi = {10.1038/s42256-020-00255-1}, year = {2020}, date = {2020-10-10}, journal = {Nature Machine Intelligence}, pages = {1--11}, keywords = {neural network, Reinforcement Learning, Transfer Learning}, pubstate = {published}, tppubtype = {article} } Close Article File doi:10.1038/s42256-020-00255-1 Close
2019
Tanneberg, Daniel; Peters, Jan; Rueckert, Elmar Intrinsic Motivation and Mental Replay enable Efficient Online Adaptation in Stochastic Recurrent Networks Journal Article In: Neural Networks – Elsevier, vol. 109, pp. 67-80, 2019, ISBN: 0893-6080, (Impact Factor of 7.197 (2017)). Links \| BibTeX \| Tags: neural network, Probabilistic Inference, RNN, spiking @article{Tanneberg2019, title = {Intrinsic Motivation and Mental Replay enable Efficient Online Adaptation in Stochastic Recurrent Networks}, author = {Daniel Tanneberg and Jan Peters and Elmar Rueckert}, url = {https://cps.unileoben.ac.at/wp/NeuralNetworks2018Tanneberg.pdf, Article File}, doi = {10.1016/j.neunet.2018.10.005}, isbn = {0893-6080}, year = {2019}, date = {2019-01-01}, journal = {Neural Networks - Elsevier}, volume = {109}, pages = {67-80}, note = {Impact Factor of 7.197 (2017)}, keywords = {neural network, Probabilistic Inference, RNN, spiking}, pubstate = {published}, tppubtype = {article} } Close Article File doi:10.1016/j.neunet.2018.10.005 Close
2018
Gondaliya, Kaushikkumar D.; Peters, Jan; Rueckert, Elmar Learning to Categorize Bug Reports with LSTM Networks Proceedings Article In: Proceedings of the International Conference on Advances in System Testing and Validation Lifecycle (VALID)., pp. 6, XPS (Xpert Publishing Services), Nice, France, 2018, ISBN: 978-1-61208-671-2, ( October 14-18, 2018). Links \| BibTeX \| Tags: Natural Language Processing, neural network, RNN @inproceedings{Gondaliya2018, title = {Learning to Categorize Bug Reports with LSTM Networks}, author = {Kaushikkumar D. Gondaliya and Jan Peters and Elmar Rueckert}, url = {https://cps.unileoben.ac.at/wp/VALID2018Gondaliya.pdf, Article File}, isbn = {978-1-61208-671-2}, year = {2018}, date = {2018-10-14}, booktitle = {Proceedings of the International Conference on Advances in System Testing and Validation Lifecycle (VALID).}, pages = {6}, publisher = {XPS (Xpert Publishing Services)}, address = {Nice, France}, note = { October 14-18, 2018}, keywords = {Natural Language Processing, neural network, RNN}, pubstate = {published}, tppubtype = {inproceedings} } Close Article File Close
2015
Calandra, Roberto; Ivaldi, Serena; Deisenroth, Marc; Rueckert, Elmar; Peters, Jan Learning Inverse Dynamics Models with Contacts Proceedings Article In: Proceedings of the International Conference on Robotics and Automation (ICRA), 2015. Links \| BibTeX \| Tags: inverse dynamics, model learning, neural network @inproceedings{Calandra2015, title = {Learning Inverse Dynamics Models with Contacts}, author = {Roberto Calandra and Serena Ivaldi and Marc Deisenroth and Elmar Rueckert and Jan Peters}, url = {https://cps.unileoben.ac.at/wp/ICRA15Calandra.pdf, Article File}, year = {2015}, date = {2015-01-01}, booktitle = {Proceedings of the International Conference on Robotics and Automation (ICRA)}, crossref = {p10794}, key = {codyco}, keywords = {inverse dynamics, model learning, neural network}, pubstate = {published}, tppubtype = {inproceedings} } Close Article File Close

Compact List without Images

Journal Articles

Tanneberg, Daniel; Rueckert, Elmar; Peters, Jan

Evolutionary training and abstraction yields algorithmic generalization of neural computers Journal Article

In: Nature Machine Intelligence, pp. 1–11, 2020.

Links | BibTeX

Tanneberg, Daniel; Peters, Jan; Rueckert, Elmar

Intrinsic Motivation and Mental Replay enable Efficient Online Adaptation in Stochastic Recurrent Networks Journal Article

In: Neural Networks – Elsevier, vol. 109, pp. 67-80, 2019, ISBN: 0893-6080, (Impact Factor of 7.197 (2017)).

Links | BibTeX

Proceedings Articles

Gondaliya, Kaushikkumar D.; Peters, Jan; Rueckert, Elmar

Learning to Categorize Bug Reports with LSTM Networks Proceedings Article

In: Proceedings of the International Conference on Advances in System Testing and Validation Lifecycle (VALID)., pp. 6, XPS (Xpert Publishing Services), Nice, France, 2018, ISBN: 978-1-61208-671-2, ( October 14-18, 2018).

Links | BibTeX

Calandra, Roberto; Ivaldi, Serena; Deisenroth, Marc; Rueckert, Elmar; Peters, Jan

Learning Inverse Dynamics Models with Contacts Proceedings Article

In: Proceedings of the International Conference on Robotics and Automation (ICRA), 2015.

Links | BibTeX